Hypothesis Testing

This course introduces hypothesis testing, covering rejection regions, p-values, Type I and Type II errors, statistical versus practical significance, power calculations, and one-mean Z and t tests. It also examines the assumptions of these tests, including the normality assumption for t tests.

Syllabus

An Introduction to Hypothesis Testing.
Z Tests for One Mean: Introduction.
Z Tests for One Mean: The Rejection Region Approach.
Z Tests for One Mean: The p-value.
Z Tests for One Mean: An Example.
One-Sided Test or Two-Sided Test?.
Type I Errors, Type II Errors, and the Power of the Test.
Statistical Significance versus Practical Significance.
The Relationship Between Confidence Intervals and Hypothesis Tests.
What is a p-value? (Updated and extended version).
Calculating Power and the Probability of a Type II Error (A One-Tailed Example).
What Factors Affect the Power of a Z Test?.
Hypothesis Testing in 17 Seconds.
t Tests for One Mean: Introduction.
t Tests for One Mean: An Example.
t Tests for One Mean: Investigating the Normality Assumption.